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An Artificial Immune System-Based Approach for the Extraction of Learning Style Stereotypes

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Knowledge-Based Software Engineering: 2018 (JCKBSE 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 108))

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Abstract

This paper presents an unsupervised computational mechanism which exhibits the ability to reveal the inherent group structure of learning patterns that pervade a given set of educational profiles. We rely on the construction of an Artificial Immune Network (AIN) of learning style exemplars by proposing a correlation-based distance metric. This choice is actually imposed by the categoric nature of the underlying data. Our work utilizes an original dataset which was derived during the conduction of an extended empirical study involving students of the Hellenic Open University. The educational profiles of the students were built by collecting their answers on a thoroughly designed questionnaire taking into account a wide range of personal characteristics and skills. The efficiency of the proposed approach was assessed in terms of cluster compactness. Specifically, we measured the average correlation deviation of the students’ education profiles from the corresponding artificial memory antibodies that represent the acquired learning style stereotypes.

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Authors and Affiliations

  1. Department of Informatics, University of Piraeus, 80, M. Karaoli & A. Dimitriou St., 18534, Piraeus, Greece

    Dionisios N. Sotiropoulos, Efthimios Alepis, Maria K. Virvou & George A. Tsihrintzis

  2. Department of Environmental Technology, Technological Educational Institute of Ionian Islands, 29100, Zakynthos, Panagoula, Greece

    Katerina Kabassi

Authors
  1. Dionisios N. Sotiropoulos
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  2. Efthimios Alepis
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  3. Katerina Kabassi
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  4. Maria K. Virvou
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  5. George A. Tsihrintzis
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Corresponding author

Correspondence to George A. Tsihrintzis .

Editor information

Editors and Affiliations

  1. Department of Informatics, University of Piraeus, Piraeus, Greece

    Maria Virvou

  2. Nippon Institute of Technology, Miyashiro, Japan

    Fumihiro Kumeno

  3. Department of Informatics, Ionian University, Corfu, Greece

    Konstantinos Oikonomou

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Sotiropoulos, D.N., Alepis, E., Kabassi, K., Virvou, M.K., Tsihrintzis, G.A. (2019). An Artificial Immune System-Based Approach for the Extraction of Learning Style Stereotypes. In: Virvou, M., Kumeno, F., Oikonomou, K. (eds) Knowledge-Based Software Engineering: 2018. JCKBSE 2018. Smart Innovation, Systems and Technologies, vol 108. Springer, Cham. https://doi.org/10.1007/978-3-319-97679-2_20

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